A New Multi-layered Approach for Automatic Text Summaries Mono-Document Based on Social Spiders

Abstract : In this paper, we propose a new multi layer approach for automatic text summarization by extraction where the first layer constitute to use two techniques of extraction: scoring of phrases, and similarity that aims to eliminate redundant phrases without losing the theme of the text. While the second layer aims to optimize the results of the previous layer by the metaheuristic based on social spiders. the objective function of the optimization is to maximize the sum of similarity between phrases of the candidate summary in order to keep the theme of the text, minimize the sum of scores in order to increase the summarization rate, this optimization also will give a candidate’s summary where the order of the phrases changes compared to the original text.The third and final layer aims to choose the best summary from the candidate summaries generated by layer optimization, we opted for the technique of voting with a simple majority.
Document type :
Conference papers
Complete list of metadatas

Cited literature [14 references]  Display  Hide  Download

https://hal.inria.fr/hal-01789959
Contributor : Hal Ifip <>
Submitted on : Friday, May 11, 2018 - 3:11:07 PM
Last modification on : Friday, May 11, 2018 - 3:13:31 PM
Long-term archiving on : Tuesday, September 25, 2018 - 5:54:07 AM

File

339159_1_En_16_Chapter.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Mohamed Boudia, Reda Hamou, Abdelmalek Amine, Mohamed Rahmani, Amine Rahmani. A New Multi-layered Approach for Automatic Text Summaries Mono-Document Based on Social Spiders. 5th International Conference on Computer Science and Its Applications (CIIA), May 2015, Saida, Algeria. pp.193-204, ⟨10.1007/978-3-319-19578-0_16⟩. ⟨hal-01789959⟩

Share

Metrics

Record views

394

Files downloads

196